The paper presents a clustering technique based on dynamic self-organizing neural networks and its application to a large-scale and highly multidimensional WWW-newsgroup-document clustering problem. The collection of 19 997 documents (e-mail messages of different Usenet-News newsgroups) available at WWW server of the School of Computer Science, Carnegie Mellon University (www.cs.cmu.edu/ TextLearning/datasets.html) has been the subject of clustering. A broad comparative analysis with nine alternative clustering techniques has also been carried out demonstrating the superiority of the proposed approach in the considered problem. © 2008 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Gorzałczany, M. B., & Rudziński, F. (2008). WWW-newsgroup-document clustering by means of dynamic self-organizing neural networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5097 LNAI, pp. 40–51). https://doi.org/10.1007/978-3-540-69731-2_5
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